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7-1 CHAPTER 7. COMPOSITE DIRECTIVITY PATTERNS FOR TAXIING AIRCRAFT This Chapter describes the process which was applied in order to create a single directivity pattern for taxiing turbojet aircraft and a single directivity pattern for taxiing turboprop aircraft. The established INM/AEDT US fleet mix (Boeker, 2007) was used to determine the weighting of the directivities for different aircraft types. The directivities used were those created as part of the development process of INM/AEDT in generating NPD curves and spectral data for taxiing aircraft as described in Chapter 4. Data fits were conducted using an energy basis in order to preserve the sound power aspect of the noise emissions. It was found for both the jets and props that using an energy average instead of arithmetic average resulted in better agreement with individual aircraft directivities. In addition to those Taxi data sources described in Chapter 3, propeller aircraft directivity data from the US Air Force Noisefile database (Mohlman, 1998) was utilized. Subsequent sections in this memorandum describe the fleet mix, the directivity equations and display the graphical representations of the directivity patterns. 7.1. Turbofan (Jet) Aircraft For consistency with INM/AEDT, the US fleet mix used for the jet directivity development is the same used for the proposed directivity behind start of takeoff roll (Boeker, 2007). That data set contained the operation of aircraft in the US for 2005. Table 7-1 lists the fleet mix as documented in briefs to the SAE A-21 Noise and Emissions Standards Committee. Using only the jet aircraft with measured directivity data behind start of takeoff roll, a normalized fleet mix was calculated and is presented in Table 7-2. A noise characterization was found for each of the jet aircraft listed in Table 7-2 except for the A330. Because the A310 has similar engines and comparable size it was used as an A330 substitute for this taxi directivity analysis. These noise characterizations came from the noise spheres used to define the noise power distance curves and spectral classes for these aircraft. TABLE 7-1 Table from Boeker (2010) - Modeling Directivity Behind the Start of Takeoff Roll Aircraft Number of ops % of Measured Fleet % of Total Fleet A319 1423985 9% 5% A320 2372032 14% 9% A330 322430 2% 1% A340 190224 1% 1% B717 333272 2% 1% B737 7088418 43% 27% B747 595303 4% 2% B757 1162127 7% 4% B767 823779 5% 3% B777 453399 3% 2% DC9 339756 2% 1% CL600 135937 8% 5% Props 6040263 23% Not Measured 3834201 15%
7-2 TABLE 7-2 Fleet Mix Used as Weightings for Taxi Directivity Plane Fleet Mix (%) Normalized Weighting (%) A319 5% 8% A320 9% 15% A330 1% 2% A340 1% 2% B717 1% 2% B737 27% 44% B747 2% 3% B757 4% 7% B767 3% 5% B777 2% 3% DC9 1% 2% CL600 5% 8% Sum: 61% 100% The directivity patterns were found by taking the one-third octave band spectral levels at the 90 degree azimuthal angle of the noise sphere (as measured from the nose). The spectrum at each angle includes 1000â of atmospheric absorption for meteorological conditions of 77oF, 70% relative humidity, and 1 atmosphere of pressure incorporated). An A-weighted level was calculated for each angle using the corrected spectra. An example directivity pattern is shown in Figure 1 where it can be seen that the levels are at their lowest to the rear and side of the aircraft. The highest taxiing noise levels towards the front of the aircraft agree with ANOPP predictions and field observations. There is no data directly in front or behind the aircraft (Figure 7-1) because this data is empirical and it is not feasible to place a microphone on the taxi way to capture emissions directly in front or behind a moving aircraft. Angle (deg) SPL (dBA) 0 10 20 30 40 50 60 70 8090100 110 120 130 140 150 160 170 180 -20-20 -10-10 00 1010 A319_001 FIGURE 7-1 Taxi directivity of A319 normalized to 90 degrees.
7-3 Two methods were considered for weighting the measured directivities of the jets in the US fleet: energy averaging and arithmetic averaging. Figure 7-2 shows the averages from both methods. Both techniques provide similar results except for the area directly in front of the aircraft. The energy average method was selected because a) the directivity patterns of the ANOPP generated spheres are computed from first principles which have their roots in sound power computations, b) the NOISEFILE empirical directivity data process involves âwandingâ a microphone vertically to better capture the sound power over a range of emission angles, and c) the Madrid empirical technique captured sound power and is reflective of energy distribution around the source. FIGURE 7-2 Comparison of arithmetic averaging of fleet-weighted levels (dB Ave) and energy averaging of fleet-weight levels (Energy). The procedure for fitting the taxi directivity data from aircraft in the US fleet mix using weightings from Table 7-2 was as follows: ï· Normalize A-weighted levels of all aircraft on the US fleet list relative to the 90o level. ï· Calculate the energy equivalent A-weighted levels and multiply by the weighting factor. ï· Take 10 Log10 of the average of the weighted energies at each angle. ï· Estimate the levels from 165 to 180 degrees by decreasing the level by 2.5 dB every 5 degrees. This drop-off rate is based on ANOPP and empirical taxi directivity data. ï· Use the weighted averages of the two aircraft (B777 and DC-9) with measured data from 20o to 0o. ï· Fit the levels from 0o to 90o and 90o to 180o separately, using fourth order polynomials. Figure 7-3 shows the plotted directivities as well as the two fits to the data.
